Using the Social Ecological Model to explore policy and institutional aspects of the school environment in relation to healthy eating and physical activity: An audit of female-only high schools in the Kingdom of Saudi Arabia
Bibliographic record
Abstract
Abstract Objective In the Kingdom of Saudi Arabia (KSA), non-communicable diseases (NCDs) cause 73% of deaths, with high body mass index (BMI) as the leading risk factor. Among adolescents, 79% reported physical inactivity (PA), 30% and 10% were living with overweight/obesity and prediabetes, respectively. Little is known about the influence of school environments in shaping healthy eating (HE) and PA behaviours. This study addressed this gap through two steps: (1) Documentary review of obesity prevention policies, (2) Assessing the school environment in relation to HE and PA. Design The documentary review consisted of two parts; Part 1: Web-searching literature, hand-searching targeted websites, and stakeholder consultations to confirm the literature findings. Part 2: School-based environmental audit employing the ISCOLE tool and the Saudi Ministry of Education Regulations for School Canteens policy. Setting Three female high schools were selected from differing economic deprivation levels in Riyadh, KSA. Participants ISCOLE questionnaires were completed by the researcher in conjunction with a staff member; photo-documentation and observations were made. Results Seventeen obesity prevention policies were identified; stakeholder consultations identified one additional policy document, and assessment highlighted challenges in policy implementation. The audit revealed notable differences between schools in HE and PA provisions Conclusion In KSA, female high schools face significant challenges regarding a school environment that supports both HE and PA. These challenges include the absence of HE provisions and lack of suitable PA facilities, coupled with a gap between policy and practice. Understanding the school context will help support the development of future obesity prevention school-based interventions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".